World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
9382
World Ranking
10502
National Ranking
117

Overview

Jin Young Choi is affiliated with Seoul National University in South Korea and has contributed extensively to the fields of Computer Science and Engineering, with a particular focus on Computer Vision and Pattern Recognition and Artificial Intelligence. Their work spans multiple subfields, including Control and Systems Engineering, Aerospace Engineering, and Statistical and Nonlinear Physics.

The scientist's main research topics include Domain Adaptation and Few-Shot Learning, Anomaly Detection Techniques and Applications, Human Pose and Action Recognition, Video Surveillance and Tracking Methods, Advanced Image and Video Retrieval Techniques, Advanced Neural Network Applications, and Imbalanced Data Classification Techniques.

Jin Young Choi's recent publications demonstrate involvement in both theoretical and application-oriented research. Notable papers include:

  • The Majority Can Help the Minority: Context-rich Minority Oversampling for Long-tailed Classification, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Influence-Balanced Loss for Imbalanced Visual Classification, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Gaussian-response correlation filter for robust visual object tracking, 2020, Neurocomputing
  • Context-Based Parking Slot Detection With a Realistic Dataset, 2020, IEEE Access
  • AutoLR: Layer-wise Pruning and Auto-tuning of Learning Rates in Fine-tuning of Deep Networks, 2021, Proceedings of the AAAI Conference on Artificial Intelligence

The scientist frequently publishes in venues such as IEEE Access, arXiv (Cornell University), Proceedings of the AAAI Conference on Artificial Intelligence, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

Their collaborations include repeated partnerships with Jongwon Choi, Byeongho Heo, Younghan Jeon, Youngmin Ro, and Dae Ung Jo, highlighting a network of co-authors involved in related research topics.

Best Publications

  • The Visual Object Tracking VOT2016 Challenge Results

    Matej Kristan;Aleš Leonardis;Jiři Matas;Michael Felsberg

  • The sixth visual object tracking VOT2018 challenge results

    Matej Kristan;Aleš Leonardis;Jiří Matas;Michael Felsberg

  • A Comprehensive Overhaul of Feature Distillation

    Byeongho Heo;Jeesoo Kim;Sangdoo Yun;Hyojin Park

  • Action-Decision Networks for Visual Tracking with Deep Reinforcement Learning

    Unknown

  • Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden Neurons

    Byeongho Heo;Minsik Lee;Sangdoo Yun;Jin Young Choi

  • The Visual Object Tracking VOT2014 challenge results

    Matej Kristan;Roman P. Pflugfelder;Ales Leonardis;Jiri Matas

  • Attentional Correlation Filter Network for Adaptive Visual Tracking

    Jongwon Choi;Hyung Jin Chang;Sangdoo Yun;Tobias Fischer

  • Intelligent visual surveillance — A survey

    In Su Kim;Hong Seok Choi;Kwang Moo Yi;Jin Young Choi

  • Sensitivity analysis of multilayer perceptron with differentiable activation functions

    Jin Young Choi;Chong-Ho Choi

  • Context-Aware Deep Feature Compression for High-Speed Visual Tracking

    Jongwon Choi;Hyung Jin Chang;Tobias Fischer;Sangdoo Yun;Sangdoo Yun

  • Visual Tracking Using Attention-Modulated Disintegration and Integration

    Jongwon Choi;Hyung Jin Chang;Jiyeoup Jeong;Yiannis Demiris

  • Symmetric Graph Convolutional Autoencoder for Unsupervised Graph Representation Learning

    Jiwoong Park;Minsik Lee;Hyung Jin Chang;Kyuewang Lee

  • The Majority Can Help The Minority: Context-rich Minority Oversampling for Long-tailed Classification.

    Unknown

  • Adaptive observer backstepping control using neural networks

    Jin Young Choi;J.A. Farrell

  • Influence-Balanced Loss for Imbalanced Visual Classification

    Seulki Park;Jongin Lim;Younghan Jeon;Jin Young Choi

  • Adaptive nonlinear guidance law considering control loop dynamics

    Dongkyoung Chwa;Jin Young Choi

  • Detection of Moving Objects with Non-stationary Cameras in 5.8ms: Bringing Motion Detection to Your Mobile Device

    Kwang Moo Yi;Kimin Yun;Soo Wan Kim;Hyung Jin Chang

  • Knowledge Distillation with Adversarial Samples Supporting Decision Boundary

    Byeongho Heo;Minsik Lee;Sangdoo Yun;Jin Young Choi

  • Detection of moving objects with a moving camera using non-panoramic background model

    Soo Wan Kim;Kimin Yun;Kwang Moo Yi;Sun Jung Kim

  • Adaptive shadow estimator for removing shadow of moving object

    JinMin Choi;Yung Jun Yoo;Jin Young Choi

  • Nonlinear adaptive control using networks of piecewise linear approximators

    J.Y. Choi;J.A. Farrell

  • Context-aware Deep Feature Compression for High-speed Visual Tracking

    Jongwon Choi;Hyung Jin Chang;Tobias Fischer;Sangdoo Yun;Sangdoo Yun

  • Observer-based adaptive guidance law considering target uncertainties and control loop dynamics

    Dongkyoung Chwa;Jin Young Choi;S.G. Anavatti

  • Sliding mode tracking control of nonholonomic wheeled mobile robots

    DongKyoung Chwa;J.H. Seo;Pyojae Kim;Jin Young Choi

  • Action-Driven Visual Object Tracking With Deep Reinforcement Learning

    Sangdoo Yun;Jongwon Choi;Youngjoon Yoo;Kimin Yun

Frequent Co-Authors

Jay A. Farrell
Jay A. Farrell University of California, Riverside
Yiannis Demiris
Yiannis Demiris Imperial College London
Nojun Kwak
Nojun Kwak Seoul National University
Seung-Ki Sul
Seung-Ki Sul Seoul National University
Tamer Basar
Tamer Basar University of Illinois at Urbana-Champaign
Kiyoung Choi
Kiyoung Choi Seoul National University
Kyoung Mu Lee
Kyoung Mu Lee Seoul National University
Mongi A. Abidi
Mongi A. Abidi University of Tennessee at Knoxville

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring computer science in the USA opens the door to many in-demand online degrees and certifications. For students interested in technical specialties, considering accredited online electrical engineering programs can expand your career options into hardware and electronics fields. These reputable degrees combine flexibility with rigorous coursework, making them attractive to working professionals.

If you are looking for quick ways to boost your qualifications, there are also certifications that pay well in areas like cybersecurity, data analysis, and cloud computing. Such specialized credentials can lead to entry-level tech positions or help you pivot faster into new roles.

For those aiming to advance their academic journey, you may consider pursuing the quickest cheapest masters degree options online, letting you save both time and money as you deepen your expertise. Frequently, computer science and related technical fields are featured among the most useful masters degrees due to their high employability and competitive salaries.

Online learning now offers flexible, accessible pathways for career development and advancement in technology and engineering. Start exploring the degree or certification that fits your goals.

Best Scientists Citing Jin Young Choi

Trending Scientists

Recently Published Articles